Workflow Templates

Overview This n8n workflow is specifically designed to monitor USDT TRC20 transactions within a specified wallet. It utilizes the public blockchain database of TronScan, requiring no API authentication, to periodically check and process transaction data. This workflow is ideal for users who need an automated solution to track their TRC20 wallet transactions. Features Automated Tracking**: Executes every 15 minutes to capture new transactions. Customizable Filters**: Tailors the tracking based on specific parameters like transaction time and wallet addresses. Data Aggregation**: Compiles transaction data into a single, structured list. Formatted Outputs**: Presents transaction data in an organized and comprehensible format. Requirements N8N (self-hosted or cloud version) setup and operational. Basic understanding of N8N workflows and nodes. Setup and Configuration Import Workflow: Load the provided JSON workflow into your N8N instance. Configure Edit Fields Node: Enter your TRC20 wallet address in the 'Your Wallet Address' field. Adjust 'Number of transactions to retrieve per request' if necessary. (Default one set to 20 which is recommanded) TronScan Data Access: The workflow accesses TronScan's public blockchain data, so no additional configuration is required for API access. Schedule Trigger Node: Defaulted to trigger every 15 minutes. Modify as per your requirements. Test the Workflow: Execute the workflow manually to ensure everything is operating correctly. How it Works Schedule Trigger: Initiates the workflow at predetermined intervals. Edit Fields: Sets up the wallet address and transaction retrieval count. TronScan Data Retrieval: Gathers transaction data from the TRC20 wallet using TronScan's public database. Split Out & Filter: Processes and filters the transaction data. Final Results: Organizes and formats the required transaction data for review. Aggregate: Consolidates all records (items) into a one comprehensive list (item). Customization Modify the filter conditions and fields to suit your tracking needs. (for example you can higher or lower the number of time to filter or IN / OUT transactions - Default is 15m/IN) Adjust the schedule trigger frequency according to your preference (default is 15m). Best Practices Regularly test the workflow to ensure consistent performance. Stay updated with any changes to the structure of TronScan's public data that might affect the workflow. Contributing Your feedback and contributions are greatly appreciated. Feel free to adapt, modify, and share enhancements with the n8n community.

This N8N workflow automates the process of sharing files from Google Drive. It includes OAuth2 authentication, batch processing, public link generation, and access status modification for efficient file handling. Suitable for users seeking to streamline their Google Drive file sharing process. sutiable for bulk actions, tested on 4.2K files folder working like charm. How It Works Initialize Workflow: The process begins with a Manual Trigger, allowing the user to start the workflow at their convenience. Folder ID Specification: A 'Set Folder ID' node where the user can enter the desired Google Drive Folder ID. List Files from Google Drive: The 'Google Drive' node lists all files within the specified folder using OAuth2 authentication. Batch Processing: The 'Loop Over Items' node processes the files in batches for efficiency. Generate Public Links: The 'Generate Download Links' node creates downloadable links for each file. Change File Access: The 'Change Status' node alters the file status to make them publicly accessible. Merge and Output: A 'Merge' node consolidates the data, preparing it for further actions or output. Set Up Steps Estimated Time**: The setup should take approximately 10-15 minutes. Initial Setup**: You'll need to provide OAuth2 credentials for Google Drive and specify a folder ID. Customization**: Adjust the batch size and file access permissions according to your needs. Detailed Descriptions**: For specific configuration details, refer to the sticky notes within the workflow. Example Item output { "link": "https://drive.google.com/u/3/uc?id=1hojqPfXchNTY8YRTNkxSo-8txK9re-V4&export=download&confirm=t&authuser=0", "name": "firefox_rNjA0ybKu7.png", "kind": "drive#permission", "id": "anyoneWithLink", "type": "anyone", "role": "reader", "allowFileDiscovery": false } You can store the output data with any data store node you want, for example save them into Excel Sheet or Airtable etc... Keywords: n8n workflow, Google Drive integration, file sharing automation, batch file processing, public link generation, OAuth2 authentication, workflow automation

Use Case This workflow is a slight variation of a workflow we're using at n8n. In most companies, employees have a lot of great ideas. That was the same for us at n8n. We wanted to make it as easy as possible to allow everyone to add their ideas to some formatted database - it should be somewhere where everyone is all the time and could add a new idea without much extra effort. Since we're using Slack, this seemed to be the perfect place to easily add ideas. In this example, we're adding the ideas to Google Sheets instead of Notion, like we do. What this workflow does This workflow waits for a webhook call within Slack, that gets fired when users use the /idea command on a bot that you will create as part of this template. It then checks the command, adds the idea to Google Sheets and notifies the user about the newly added idea as you can see below: Creating your Slack bot Visit https://api.slack.com/apps, click on New App and choose a name and workspace. Click on OAuth & Permissions and scroll down to Scopes -> Bot token Scopes Add the chat:write scope Head over to Slash Commands and click on Create New Command Use /idea as the command Copy the test URL from the Webhook node into Request URL Add whatever feels best to the description and usage hint Go to Install app and click install Setup Create a Google Sheets document with the columns Name and Creator Add your Google credentials Fill the Set me up node. Create your Slack app (see other sticky) Click Test workflow and use the /idea comment in Slack Activate the workflow and exchange the Request URL with the production URL from the webhook How to adjust it to your needs You can adjust the table in Google Sheets and for example, add different types of ideas or areas that they impact Rename the Slack command as it works best for you How to enhance this workflow At n8n we use this workflow in combination with some others. E.g. we have the following things on top: We additionally have a /bug Slack command that adds a new bug to Linear. Here we're using AI to classify the bugs and move it to the right team. (Bug command workflow and Ai Classifier workflow) We also added other types, like /pain to be less solution-driven To make it easier for everyone to give input, we added a Votes column that allows everyone to vote on ideas/pain points in the list We're also running a workflow once a week that highlights the most popular new ideas and the most active voters

Intro This template is for project managers, team leads, or anyone who wants to automatically remind teammates of tasks due today—no manual copy‑and‑paste required. How it works Schedule Trigger runs every morning at 8 AM. Google Sheets node reads your “Tasks” sheet. If node filters rows where Due Date = today. Summarize (ChatGPT HTTP Request) generates a friendly reminder per person. Message a model sends the prompt to your ChatGPT Assistant and returns the AI response. Send a message (Gmail) emails each assignee their personalized reminder. Required Google Sheet Structure | Column Name | Type | Example | Notes | |-------------|--------|---------------------------|-------------------------| | Name | string | Alice Johnson | Person to remind | | Email | string | user@example.com | Recipient email address | | Task | string | Submit quarterly report | Task description | | Due Date | date | 2025‑07‑29 | Format: YYYY‑MM‑DD | Detailed Setup Steps Google Sheets Create your sheet with the columns above. In n8n → Credentials, add Google Sheets API (do not include real sheet IDs in the name). ChatGPT Assistant In the OpenAI Dashboard → Assistants, click Create Assistant. Choose a model (e.g., gpt-4), copy the Assistant ID. In n8n → Credentials → OpenAI, add your API Key and Assistant ID. Gmail In n8n → Credentials → Gmail (OAuth2 or SMTP), connect your account without embedding your real address in the credential name. Import & Configure Export this workflow’s JSON (three‑dot menu → Export). Paste it under Template Code in the Creator form. In each node, select your Google Sheets, OpenAI, and Gmail credentials. Sticky Notes A note on the Schedule node: “Set your desired run time.” A note on the ChatGPT node: “Customizes reminder text.” A note on the Gmail node: “Sends reminder email.” Customization Guidance Change schedule: edit the Cron expression in **Schedule Trigger. Adjust tone**: modify the system prompt in your ChatGPT Assistant. Email format: update **Subject and Body in the Gmail node. Batch processing: insert a **SplitInBatches node before Summarize for large sheets. Troubleshooting Ensure your Google Sheet is shared with the connected service account. Verify Due Date format (YYYY‑MM‑DD). If ChatGPT fails, check your API key and quota. Security & Best Practices Do not** hard‑code API keys, sheet IDs, or real emails. Use n8n Credentials or environment variables only. Remove any private information before submitting.

This workflow contains community nodes that are only compatible with the self-hosted version of n8n. Auto-Publish Technology News to WordPress with GPT-4o Content Enhancement This comprehensive automated workflow fetches the latest technology news every 3 hours, leverages OpenAI's GPT-4o to analyze and transform news articles into engaging blog posts, and publishes them directly to your WordPress website. The system includes robust error handling with email notifications to ensure smooth operation, making it perfect for keeping your blog updated with fresh, AI-enhanced content without manual intervention. What This Workflow Does The workflow demonstrates several key automation concepts: Schedule recurring automated tasks with precise timing control Fetch data from external APIs (News API) with proper authentication Process content in batches for efficient handling Use AI for intelligent content transformation and enhancement Format and structure data for publishing platforms Publish to content management systems automatically Implement comprehensive error handling and notifications Prerequisites & Requirements Before setting up this workflow, ensure you have: Required API Credentials News API Key**: Sign up at newsapi.org for free access to news articles OpenAI API Key**: Create an account at platform.openai.com and generate an API key with GPT-4o access WordPress API Access**: Your WordPress site must have REST API enabled (default in modern WordPress) SMTP Email Account**: For error notifications (Gmail, Outlook, or custom SMTP) WordPress Setup WordPress 4.7+ with REST API enabled Application password or JWT authentication configured Appropriate user permissions for post creation n8n Configuration n8n instance (cloud or self-hosted) Proper credential storage for all external services Step-by-Step Setup Instructions Step 1: Configure News API Credentials Navigate to n8n Credentials section Create new "News API" credential Enter your API key from newsapi.org Test the connection to ensure it's working Step 2: Set Up OpenAI Integration Add OpenAI credentials in n8n Enter your API key from OpenAI platform Ensure you have access to GPT-4o model Configure rate limiting if needed Step 3: WordPress Connection Create WordPress API credentials Use either application password or JWT token Test connection with a sample API call Verify post creation permissions Step 4: Email Notifications Setup Configure SMTP credentials for error handling Set recipient email addresses Customize error message templates Test email delivery Step 5: Import and Configure Workflow Import the JSON workflow into your n8n instance Update the "News API Batch Processor" node settings Modify the schedule trigger frequency if needed (default: every 3 hours) Customize the AI prompt in the OpenAI node for your brand voice Adjust WordPress post settings (categories, tags, status) Customization Options Content Filtering Modify news categories (technology, business, science, etc.) Adjust country selection for regional news Change article count per batch (default: 10) AI Content Enhancement Customize the system prompt for different writing styles Adjust creativity level (temperature parameter) Modify output length and format requirements Add specific instructions for your brand voice Publishing Settings Configure post status (draft, publish, private) Set default categories and tags Add custom fields or metadata Schedule publishing times Error Handling Customize error notification recipients Modify retry logic for failed requests Add additional error handling branches Configure logging levels Workflow Architecture The workflow consists of 8 strategically connected nodes: Schedule Trigger: Initiates the workflow every 3 hours HTTP Request - News API: Fetches latest technology headlines News API Batch Processor: Splits articles for individual processing OpenAI - Analyze News: Transforms articles into engaging blog posts Set Blog Post: Formats data for WordPress publication WordPress - Create Post: Publishes content to your website Error Handler: Catches and processes any workflow failures Send Error Email: Notifies administrators of issues Expected Output Each processed article generates: SEO-optimized blog post title Well-structured HTML content with headings and paragraphs Engaging introduction and conclusion Source attribution and links Automatic publishing to WordPress Metadata including publish date and source URL Monitoring & Maintenance Performance Monitoring Check execution logs regularly Monitor API rate limits and usage Review generated content quality Track WordPress post metrics Regular Updates Update API keys when they expire Adjust content filters based on performance Refine AI prompts for better output Monitor and update error handling rules Troubleshooting Common Issues API Rate Limits Reduce batch size if hitting News API limits Implement delays between OpenAI requests Monitor usage dashboards Content Quality Refine system prompts for better AI output Add content validation steps Implement human review queues for sensitive topics WordPress Publishing Verify user permissions and authentication Check for plugin conflicts Ensure proper REST API configuration This template provides a solid foundation for automated content creation and can be extended with additional features like social media posting, content scheduling, or advanced analytics integration.

⚠️ Note: This template requires a community node and works only on self-hosted n8n installations. It uses the Typhoon OCR Python package and custom command execution. Make sure to install required dependencies locally. Who is this for? This template is for developers, operations teams, and automation builders in Thailand (or any Thai-speaking environment) who regularly process PDFs or scanned documents in Thai and want to extract structured text into a Google Sheet. It is ideal for: Local government document processing Thai-language enterprise paperwork AI automation pipelines requiring Thai OCR What problem does this solve? Typhoon OCR is one of the most accurate OCR tools for Thai text. However, integrating it into an end-to-end workflow usually requires manual scripting and data wrangling. This template solves that by: Running Typhoon OCR on PDF files Using AI to extract structured data fields Automatically storing results in Google Sheets What this workflow does Trigger: Run manually or from any automation source Read Files: Load local PDF files from a doc/ folder Execute Command: Run Typhoon OCR on each file using a Python command LLM Extraction: Send the OCR markdown to an AI model (e.g., GPT-4 or OpenRouter) to extract fields Code Node: Parse the LLM output as JSON Google Sheets: Append structured data into a spreadsheet Setup 1. Install Requirements Python 3.10+ typhoon-ocr: pip install typhoon-ocr Install Poppler and add to system PATH (needed for pdftoppm, pdfinfo) 2. Create folders Create a folder called doc in the same directory where n8n runs (or mount it via Docker) 3. Google Sheet Create a Google Sheet with the following column headers: | book\_id | date | subject | detail | signed\_by | signed\_by2 | contact | download\_url | | -------- | ---- | ------- | ------ | ---------- | ----------- | ------- | ------------- | You can use this example Google Sheet as a reference. 4. API Key Export your TYPHOON_OCR_API_KEY and OPENAI_API_KEY in your environment (or set inside the command string in Execute Command node). How to customize this workflow Replace the LLM provider in the Basic LLM Chain node (currently supports OpenRouter) Change output fields to match your data structure (adjust the prompt and Google Sheet headers) Add trigger nodes (e.g., Dropbox Upload, Webhook) to automate input About Typhoon OCR Typhoon is a multilingual LLM and toolkit optimized for Thai NLP. It includes typhoon-ocr, a Python OCR library designed for Thai-centric documents. It is open-source, highly accurate, and works well in automation pipelines. Perfect for government paperwork, PDF reports, and multilingual documents in Southeast Asia.

This n8n template lets you instantly serve batches of inspirational quotes via a webhook using the free ZenQuotes API. It’s perfect for developers, content creators, community managers, or educators who want to add dynamic, uplifting content to websites, chatbots, or internal tools—without writing custom backend code. 🔧 How it works A Webhook node listens for incoming HTTP requests on your chosen path. Get Random Quote from ZenQuotes sends an HTTP Request to https://zenquotes.io/api/random?count=5 and retrieves five random quotes. Format data uses a Set node to combine each quote (q) and author (a) into a single string: "“quote” – author". Send response returns a JSON array of objects { quote, author } back to the caller. 👤 Who is it for? This workflow is ideal for: Developers building motivational Slack or Discord bots. Website owners adding on-demand quote widgets. Educators or trainers sharing daily inspiration via webhooks. Anyone learning webhook handling and API integration in n8n. 🗂️ Response Structure Your webhook response will be a JSON array, for example: [ { "quote": "Life is what happens when you're busy making other plans.", "author": "John Lennon" }, { "quote": "Be yourself; everyone else is already taken.", "author": "Oscar Wilde" } ] ⚙️ Setup Instructions Import the workflow JSON into your n8n instance. In the Webhook node, set your desired path (e.g., /inspire). (Optional) Change the count parameter in the HTTP Request node to fetch more or fewer quotes. Activate the workflow. Test by sending an HTTP GET or POST to https://<your-n8n-domain>/webhook/<path>.

This workflow contains community nodes that are only compatible with the self-hosted version of n8n. How it works This workflow demonstrates how to create a resilient AI Agent that automatically falls back to a different language model if the primary one fails. This is useful for handling API errors, rate limits, or model outages without interrupting your process. State Initialization: The Agent Variables node initializes a fail_count to 0. This counter tracks how many models have been attempted. Dynamic Model Selection: The Fallback Models (a LangChain Code node) acts as a router. It receives a list of all connected AI models and, based on the current fail_count, selects which one to use for this attempt (0 for the first model, 1 for the second, etc.). Agent Execution: The AI Agent node attempts to run your prompt using the model selected by the router. The Fallback Loop: On Success: The workflow completes successfully. On Error: If the AI Agent node fails, its "On Error" output is triggered. This path loops back to the Agent Variables node, which increments the fail_count by 1. The process then repeats, causing the Fallback Models router to select the next model in the list. Final Failure: If all connected models are tried and fail, the workflow will stop with an error. Set up steps Setup time: ~3-5 minutes Configure Credentials: Ensure you have the necessary credentials (e.g., for OpenAI, Google AI) configured in your n8n instance. Define Your Model Chain: Add the AI model nodes you want to use to the canvas (e.g., OpenAI, Google Gemini, Anthropic). Connect them to the Fallback Models node. Important: The order in which you connect the models determines the fallback order. The model nodes first created/connected will be tried first. Set Your Prompt: Open the AI Agent node and enter the prompt you want to execute. Test: Run the workflow. To test the fallback logic, you can temporarily disable the First Model node or configure it with invalid credentials to force an error.

Who is this tempate for? This workflow powers a simple yet effective customer and sales support chatbot for your webshop. It's perfect for solopreneurs who want to automate customer interactions without relying on expensive or complex support tools. How it works? The chatbot listens to user requests—such as checking product availability—and automatically handles the following Fetches product information from a Google Sheet Answers customer queries Places an order Updates the stock after a successful purchase Everything runs through a single Google Sheet used for both stock tracking and order management. Setup Instructions Before you begin, connect your Google Sheets credentials by following this guide: This will be used to connect all the tools to Google Sheets 👉 Setup Google sheets credentials Get Stock Open "Get Stock" tool node and select the Google sheet credentials you created. Choose the correct google sheet document and sheet name and you are done. Place order Go to your "Place Order" tool node and select the Google sheet credentials you have created. Choose the correct google sheet document and sheet name. Update Stock - Open your "Update Stock" tool node and select the Google sheet credentials you have created. Choose the correct google sheet document and sheet name. In "Mapping Column Mode" section select map each column manually. In "Column to match on" select the column with a unique identifier (e.g., Product ID) to match stock items. In values to update section, add only the column(s) that need to be updated—usually the stock count. AI Agent node Adjust the prompt according to your use case and customize what you need. Google Sheet Template Stock sheet |Case ID|Phone Model|Case Name|Case Type|Image URL|Quantity Avaialble|Initital Inventory|Sold| |-|-|-|-|-|-|-|-| |1023|Iphone 14 pro|Black Leather|Magsafe|https://example.com/url|90|100|10 Order sheet |Case ID|Phone Model|Case Name|Name|Phone Number|Address| |-|-|-|-|-|-| |1023|Black Leather |Iphone 14 pro|Fernando Torres|9998898888|Paris, France

Who is this for? Content strategists analyzing web page semantic content SEO professionals conducting entity-based analysis Data analysts extracting structured data from web pages Marketers researching competitor content strategies Researchers organizing and categorizing web content Anyone needing to automatically extract entities from web pages What problem is this workflow solving? Manually identifying and categorizing entities (people, organizations, locations, etc.) on web pages is time-consuming and error-prone. This workflow solves this challenge by: Automating the extraction of named entities from any web page Leveraging Google's powerful Natural Language API for accurate entity recognition Processing web pages through a simple webhook interface Providing structured entity data that can be used for analysis or further processing Eliminating hours of manual content analysis and categorization What this workflow does This workflow creates an automated pipeline between a webhook and Google's Natural Language API to: Receive a URL through a webhook endpoint Fetch the HTML content from the specified URL Clean and prepare the HTML for processing Submit the HTML to Google's Natural Language API for entity analysis Return the structured entity data through the webhook response Extract entities including people, organizations, locations, and more with their salience scores Setup Prerequisites: An n8n instance (cloud or self-hosted) Google Cloud Platform account with Natural Language API enabled Google API key with access to the Natural Language API Google Cloud Setup: Create a project in Google Cloud Platform Enable the Natural Language API for your project Create an API key with access to the Natural Language API Copy your API key for use in the workflow n8n Setup: Import the workflow JSON into your n8n instance Replace "YOUR-GOOGLE-API-KEY" in the "Google Entities" node with your actual API key Activate the workflow to enable the webhook endpoint Copy the webhook URL from the "Webhook" node for later use Testing: Use a tool like Postman or cURL to send a POST request to your webhook URL Include a JSON body with the URL you want to analyze: {"url": "https://example.com"} Verify that you receive a response containing the entity analysis data How to customize this workflow to your needs Analyzing Specific Entity Modify the "Google Entities" node parameters to include entityType filters Add a "Function" node after "Google Entities" to filter specific entity types Create conditions to extract only entities of interest (people, organizations, etc.) Processing Multiple URLs in Batch: Replace the webhook with a different trigger (HTTP Request, Google Sheets, etc.) Add a "Split In Batches" node to process multiple URLs Use a "Merge" node to combine results before sending the response Enhancing Entity Data: Add additional API calls to enrich extracted entities with more information Implement sentiment analysis alongside entity extraction Create a data transformation node to format entities by type or relevance Additional Notes This workflow respects Google's API rate limits by processing one URL at a time The Natural Language API may not identify all entities on a page, particularly for highly technical content HTML content is trimmed to 100,000 characters if longer to avoid API limitations Consider legal and privacy implications when analyzing and storing entity data from web pages You may want to adjust the HTML cleaning process for specific website structures ❤️ Hueston SEO Team

Daily YouTrack In-Progress Tasks Summary to Discord by Assignee Keep your team in sync with a daily summary of tasks currently In Progress in YouTrack — automatically posted to your Discord channel. This workflow queries issues, filters them by status, groups them by assignee and priority, and sends a formatted message to Discord. It's perfect for teams that need a lightweight, automated stand-up report. > 📝 This workflow uses Discord as an example. You can easily replace the messaging integration with Slack, Mattermost, MS Teams, or any other platform that supports incoming webhooks. Use Case Remote development teams using YouTrack + Discord Replacing daily stand-up meetings with async updates Project managers needing quick visibility into active tasks Features Scheduled** daily execution (default: weekdays at 09:00) Status filter**: only issues marked as In Progress Grouping** by assignee and priority Custom mapping** for user mentions (YouTrack → Discord) Clean Markdown output** for Discord, with direct task links Setup Instructions YouTrack Configuration Get a permanent token: Go to your YouTrack profile → Account Security → Authentication Create a new permanent token with "Read Issue" permissions Copy the token value Set the base API URL: Format: https://yourdomain.youtrack.cloud/api/issues Replace yourdomain with your actual YouTrack instance Identify custom field IDs: Method 1: Go to YouTrack → Administration → Custom Fields → find your "Status" field and note its ID Method 2: Use API call GET /api/admin/customFieldSettings/customFields to list all field IDs Method 3: Inspect a task's API response and look for field IDs in the customFields array Example Status field ID: 105-0 or 142-1 Discord Configuration Create a webhook URL in your Discord server: Server Settings → Integrations → Webhooks → New Webhook Choose target channel and copy the webhook URL Extract webhook ID from URL (numbers after /webhooks/) Environment Variables & Placeholders | Placeholder | Description | |-------------|-------------| | {{API_URL}} | Your YouTrack API base URL | | {{TOKEN}} | YouTrack permanent token | | {{FIELD_ID}} | ID of the "Status" custom field | | {{QUERY_FIELDS}} | Fields to fetch (e.g., summary, id) | | {{PROJECT_LINK}} | Link to your YouTrack project | | {{USER_X}} | YouTrack usernames | | {{DISCORD_ID_X}} | Discord mentions or usernames | | {{NAME_X}} | Display names | | {{WEBHOOK_ID}} | Discord webhook ID | | {{DISCORD_CHANNEL}} | Discord channel name | | {{CREDENTIAL_ID}} | Your credential ID in n8n | Testing the Workflow Test YouTrack connection: Execute the "HTTP Request YT" node individually Verify that issues are returned from your YouTrack instance Check if the Status field ID is correctly filtering tasks Verify filtering: Run the "Filter fields" node Confirm only "In Progress" tasks pass through Check message formatting: Execute the "Discord message" node Review the generated message content and formatting Test Discord delivery: Run the complete workflow manually Verify the message appears in your Discord channel Schedule verification: Enable the workflow Test weekend skip functionality by temporarily changing dates Customization Tips Language**: All labels/messages are in English — customize if needed User mapping**: Adjust assignee → Discord mention logic in the message builder Priorities**: Update the priorityMap to reflect your own naming structure Schedule**: Modify the trigger time in the Schedule Trigger node Alternative platforms**: Swap out the Discord webhook for another messaging service if preferred

Real-time Weather Forecasts with MCP Tools This n8n workflow demonstrates how to integrate real-time weather intelligence into any automation using the Model Context Protocol (MCP). Get current conditions and 5-day forecasts with natural language queries like "What's the weather like in Miami?" or "Will it rain next Tuesday in Seattle?" - all powered by live weather data and AI. Good to know No API keys required - uses hosted MCP weather server with built-in WorldWeatherOnline integration Provides current conditions and detailed 5-day forecasts Natural language queries work for any location worldwide Powered by WorldWeatherOnline - the world's most accurate weather system Fully preconfigured and ready to run out-of-the-box Enterprise-ready with error handling and rate limiting How it works Natural Language Input**: Receives weather queries via webhook, chat, email, or voice AI Agent Processing**: n8n Agent node interprets requests and determines: Location extraction from natural language Weather data type needed (current or 5-day forecast) Response formatting preferences MCP Weather Tool**: Live hosted server provides: Real-time current conditions (temperature, humidity, wind, conditions) 5-day detailed forecasts with daily highs/lows Weather descriptions and condition codes Powered by WorldWeatherOnline's premium data Intelligent Responses**: AI formats weather data into: Conversational natural language responses Structured data for downstream automation Action-triggering data for workflows How to use Import the workflow into n8n from the template Add your preferred AI model API key to the Agent node Customize the system prompt for your specific use case Connect to your preferred input/output channels Run and start querying weather with natural language Use Cases Smart Home Automation**: "Turn on sprinklers if no rain forecast for 3 days" Travel Planning**: "Check weather for my Paris trip next week" Event Management**: "Will outdoor wedding conditions be good Saturday?" Agriculture/Farming**: "Check 5-day forecast for planting schedule" Logistics**: "Delay shipping if severe weather forecast in delivery zone" Personal Assistant**: "Should I wear a jacket today in Chicago?" Sports/Recreation**: "Surf conditions and wind forecast for weekend" Construction**: "Safe working conditions for outdoor project this week" Requirements n8n instance (cloud or self-hosted) AI model provider account (OpenAI, Anthropic, Google, etc.) Internet connection for MCP weather server access Optional: Webhook endpoints for external integrations Customizing this workflow Location Intelligence**: Add geocoding for address-to-coordinates conversion Data Storage**: Save weather history to databases for trend analysis Dashboard Integration**: Connect to Grafana, Tableau, or custom visualizations Voice Integration**: Add speech-to-text for voice weather queries Scheduling**: Set up automated daily/weekly weather briefings Conditional Logic**: Trigger different actions based on weather conditions Sample Input/Output Natural Language Queries: "What's the weather like in Miami?" "Will it rain next Tuesday in Seattle?" "5-day forecast for London" "Temperature in Tokyo tomorrow" "Weather conditions for outdoor event Saturday" Rich Responses: { "location": "Miami, FL", "current": { "temperature": "78°F", "condition": "Partly Cloudy", "humidity": "65%", "wind": "10 mph SE" }, "forecast": { "today": "High 82°F, Low 71°F, 20% rain", "tomorrow": "High 85°F, Low 73°F, Sunny" }, "ai_summary": "Perfect beach weather in Miami today! Partly cloudy with comfortable temperatures and light winds." } Why This Workflow is Unique Zero Setup Weather Data**: No API key management - MCP server handles everything World-Class Accuracy**: Powered by WorldWeatherOnline's premium weather data AI-Powered Intelligence**: Natural language understanding of complex weather queries Enterprise Ready**: Built-in error handling, rate limiting, and reliability Global Coverage**: Worldwide weather data with location intelligence Action-Oriented**: Designed for automation decisions, not just information display Transform your automations with intelligent weather awareness powered by the world's most accurate weather system! 🧪 Setup Steps ✅ The Agent node is already configured: The system prompt is included The tool endpoint is pre-set All you need to do is: Add your AI model API key to the existing Agent credential Hit run and you're done ✅ 🔗 Full project link: Github: weathertrax-mcp-agent-demo